#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jun  4 11:05:37 2023

@author: shenzheqi
"""

case_dir = "./"
from netCDF4 import Dataset
PData = Dataset(case_dir+"parameters.nc")
parameters = PData["paras"]
import numpy as np
import matplotlib.pyplot as plt
plt.figure(figsize=(12,5))
for j in range(4):
    plt.subplot(2,2,j+1)
    plt.plot(parameters[:,j],'k--')
    plt.plot(np.mean(parameters[:,j],axis=1),'r',lw=3,label="ensemble mean")
    if j==0:
        plt.legend(fontsize=14)
        plt.yticks(np.arange(0.1,0.26,0.05),fontsize=14)
        plt.title('vdc1',fontsize=15)
        plt.xticks([0,36,72],[],fontsize=14)
    if j==1:
        plt.yticks(np.arange(0.005,0.015,0.003),fontsize=14)
        plt.title('vdc_eq',fontsize=15)
        plt.xticks([0,36,72],[],fontsize=14)
    if j==2:
        plt.yticks(np.arange(0.05,0.25,0.05),fontsize=14)
        plt.title('vdc_psim',fontsize=15)
        plt.xticks([0,36,72],[2006,2007,2008],fontsize=14)
        plt.xlabel('Time',fontsize=14)
    if j==3:
        plt.yticks(np.arange(0.5,1.7,0.3),fontsize=14)
        plt.title('vdc_ban',fontsize=15)
        plt.xticks([0,36,72],[2006,2007,2008],fontsize=14)
        plt.xlabel('Time',fontsize=14)
    plt.grid(axis='x')
plt.savefig("fig3.eps")